This invention relates generally to social networks, and more particularly to invitations in a social network.
Social network environments present many types of invitations to users. Examples of an invitation include an advertisement, a request to join a group, a request for an information exchange, a survey, a request to write a blog entry, a request to verify a photo tag, and so forth.
It is often useful to be able to characterize major differences between two sets of users in a social network. A probability function may be useful for predicting the likelihood of a positive or negative response by a user to an invitation. In a co-pending application, the probability function may be determined from user information including keywords in selected user profiles and from the users' responses to a prior invitation. See U.S. patent application Ser. No. 11/893,797 filed on Aug. 16, 2007, entitled “System and Method for Invitation Targeting in a Web-Based Social Network.” However, those techniques do not allow for a determination of characteristics of the users who respond and/or do not respond to the invitation (e.g., what distinguishes the users who respond from the users who do not respond, how do the users who responded differ demographically from users in general and from users who do not respond, etc.). For example, the number of users who respond may not be sufficient to provide useful information or make statistically significant inferences. The raw information about the keywords used in determining the probability function may be insufficient to provide useful details about a correlation between user information and the users. Moreover, data manipulation used in determining the probability function may reduce the user information including the keywords to a format that is not easily interpreted and make it difficult to extract insights directly from the keywords or the probability function results.